Big data development services: Your big leap toward hyper-intelligent decisions and seamless operations

Limited ability to experiment at scale: Without regular revenue streams, funding research and development may be challenging. 

Solution: Check the idea's feasibility and start with proof-of-concept so you won't get stuck in the middle of the project with something that cannot be implemented. Prioritize the features and start with delivering an MVP. You’ll make key features available to users and will be able to add new features gradually. In addition to learning what users love about your solution and possible stumbling blocks, you’ll get the chance to win investors’ trust and interest. 

Tight budgets may slow down the scaling of big data systems. As your product wins more users, it needs additional storage and processing resources, which can significantly increase cloud costs. 

Solution: Plan cost optimization strategies from day one. These can include open-source tools, spot instances for cloud savings, and auto-scaling cloud features. You can also consider data-sharing partnerships to access external insights without data collection or purchase costs.

Data silos: Your data may be scattered across systems — some of which are over a decade old — and sitting there disconnected instead of fueling insights. 

Solution: This is the point where most data-driven transformations begin. Our experts will analyze your situation, map out data sources and types, and recommend the most efficient consolidation and integration strategy.   

High operational costs: As data grows, so do storage and processing costs — sometimes unpredictably. 

Solution: This can happen unless you manage your costs wisely. Examples of how to optimize costs include using lean data retention policies and catching mechanisms to reduce the load, splitting data lakes into “warm” and “cold” zones, monitoring consumption, and setting up budget alerts. 

A blurred border between “it’s a must-have” and “it’s a money drain”: For SMBs, it’s especially difficult to understand if investment in big data is beneficial or if traditional systems will do better and cost-effectively. 

Solution: Involve professional consultants to conduct a thorough cost-benefit analysis of big data implementation.

Legacy tools: Once you’ve invested in different solutions, you may find it complicated to justify the adoption of modern tools. 

Solution: Start with a cost-benefit analysis for your big data initiative, catalog your existing systems, and draft a robust app modernization plan. 

High costs of scaling on-premises infrastructure: Buying and maintaining servers is expensive, especially as data volume skyrockets. 

Solution: To handle extra demand during peak times, you can consider a mix of on-premises and cloud storage while keeping your main operations in-house. Alternatively, you may choose to migrate to the cloud entirely. 

Potentially slow decision-making: Many layers of approvals, distributed teams, or departmental silos can slow down decision-making and implementation. 

Solution: Encourage collaboration between departments and create fast-track approval processes for pilot projects. 

Corporate culture can limit innovation: A focus on stability can make the company hesitant to try new things. 
Solution: Create testing environments or innovation labs where teams can experiment without disrupting regular business processes.

• Detect disease patterns in patient data for early diagnosis. 

• Use biometric data to identify early signs of illness before symptoms manifest. 

• Identify outbreaks before they escalate. 

• Analyze research papers and health records to uncover optimal treatments. 

• Forecast patient risks and outcomes. 

• Accelerate drug discovery with molecular simulations and side effect predictions. 

Some of the well-known brands that set the standards: Pfizer, Roche, Novartis, Mayo Clinic, Cleveland Clinic, Philips Healthcare, Fitbit.

• Adjust prices in real time based on demand, competitors, and user behavior. 

• Recommend products using customer preferences and buying history. 

• Forecast demand to maintain optimal stock levels and prevent shortages. 

• Analyze foot traffic to optimize staffing and store layouts. 

• Prevent equipment breakdowns with predictive maintenance. 

• Boost loyalty with personalized discounts and exclusive offers. 

Some of the well-known brands that set the standards: Amazon, Walmart, Target, IKEA, Sephora, Nike, Zara (Inditex Group), H&M.

• Prevent outages with real-time infrastructure health monitoring. 

• Identify at-risk customers and implement proactive retention strategies. 

• Allocate network resources dynamically based on user demand. 

• Analyze customer behavior to deliver personalized service. 

• Detect cybersecurity threats before they disrupt operations. 

• Optimize call center performance with AI-driven automation and chatbots. 

Some of the well-known brands that set the standards: AT&T, Verizon, Vodafone, T-Mobile.

• Monitor energy usage patterns and dynamically allocate resources to meet current demand. 

• Monitor grid stability and identify potential faults or overloads to initiate preventive measures. 

• Forecast energy demand to ensure optimal energy flow and prevent imbalances. 

• Improve the accuracy of locating reserves and enhance drilling efficiency. 

• Predict equipment failures, allowing for timely maintenance and reducing downtime. 

• Continuously assess the condition of machinery and immediately respond to detected anomalies. 

• Optimize the procurement and distribution processes.  

Some of the well-known brands that set the standards: American Electric Power, Austin Energy, City of Palo Alto Utilities, Vattenfall, Saudi Aramco, ExxonMobil, Royal Dutch Shell

• Analyze real-time traffic data, weather conditions, and historical delivery times to optimize routes and avoid delays. 

• Monitor vehicle health and performance to prevent breakdowns. 

• Analyze demand fluctuations, optimize warehouse space utilization, and ensure efficient inventory management. 

• Track product origins, storage, and transportation conditions. 

Some of the well-known brands that set the standards: FedEx, DHL, CMA CGM, UPS.